10 Bits: the Data News Hotlist

This week’s list of data news highlights covers January 5 – 11, 2019, and includes articles about an AI system that can identify genetic diseases by analyzing faces and a new AI app that can detect overdoses.

Intel, sustainability non-profit Resolve, and several other groups have developed TrailGuard AI, an AI system that combines cameras and computer vision to detect and alert park rangers to the presence of potential poachers. The smart cameras in TrailGuard AI are the size of a human finger and use an on-device algorithm to analyze frames for humans or vehicles. A prototype of the system, which the groups have improved upon by reducing the number of false positive reports, helped authorities capture 20 gangs of poachers over 15 months at Serengeti National Park in Tanzania.

DARPA has created the Knowledge-directed Artificial Intelligence Reasoning Over Schemas (KAIROS) program, which has the goal of developing an AI system capable of making correlations between seemingly unrelated world events. The program plans to classify and cluster large volumes of data, including unstructured data such as multimedia information, to translate seemingly unrelated events into narrative structures, or “schemas.” The program plans to then use these schemas to forecast future events.

Researchers from several universities and genetic analysis firm FDNA have developed an AI technology called DeepGestalt that accurately identifies rare genetic disorders by analyzing a photograph of a patient’s face. The researchers trained DeepGestalt on 17,000 facial images of patients with over 200 genetic syndromes. DeepGestalt outperformed clinicians in three trials, including a trial where it suggested potential syndromes after analyzing images.

The UK National Health Service (NHS) has released a long term plan, which outlines how it intends to modernize and save half a million lives in the next 10 years. In particular, the plan describes how beginning in 2019, NHS will map the genomes of all children with cancer to improve treatment outcomes. Early research predicts that this approach could result in a 50 percent increase in actionable information that can improve treatment decisions.

Researchers from the University of Washington have developed an app that accurately detects if a person has begun to overdose on drugs. The apps uses sonar to tell if someone’s breathing has slowed or stopped, which are both signs of an overdose, by measuring the rate of reflected sound waves. When tested on 194 participants at a supervised injection facility, the app identified individuals who had stopped breathing with 97.7 percent accuracy and those with slowed breathing with 89.3 percent accuracy.

Goodwill is using artificial intelligence to authenticate luxury items sold on its website. To do so, the firm has partnered with product authentication firm Entrupy, which has developed a system that uses computer vision technology to verify items, such as Burberry handbags, with over 99 percent accuracy. Goodwill employees will use a scanner and mobile app to verify luxury items, and a financial guarantee will accompany each verified item.

Chicago has redesigned its 311 system, which citizens access for non-emergency services, to make it more data driven. For example, citizens can share more data about their complaints, such as uploading images about potholes, and track the progress of their requests through an app that has roughly 100 unique request categories. The city’s managers also have a customized analytics dashboards, allowing the city to gain greater insight into issues plaguing the city.

Rep. Virginia Foxx (R-NC) has reintroduced the Grant Reporting Efficiency and Agreements Transparency (GREAT) Act, which aims to standardize the federal grant reporting process to make government spending more efficient. The legislation would require the creation of standardized data taxonomy for all data elements grant recipients report. The legislation would also require the Office of Management and Budget to publish the data on a government website.

Sporting goods company Callaway used an AI system to make its new golf club called the Epic Flash. The system cycled through 15,000 possible iterations of clubface designs to find the optimal design to increase a golfer’s driving distance. The result is a clubface that, unlike conventional drivers, is thinnest in the center and has dozens of ripples that make no discernable pattern to the human eye.

The U.S. Food and Drug Administration (FDA) has developed several updates to its proposed Digital Health Precertification (Pre-Cert) Program, which aims to make the regulatory approval process faster and better suited for medical software, such as diagnostic algorithms. The FDA has published an explanation of the regulatory framework for the Pre-Cert program, which will evaluate companies to determine if their software products are likely to be safe and effective, rather than the current approach of subjecting the design process of each new product to a rigorous evaluation. The FDA has also published a test plan and working model explaining how the Pre-Cert process would work and could be improved upon in the future. The FDA will pilot the Pre-Cert program in 2019.

Michael McLaughlin is a research assistant at the Center for Data Innovation. He researches and writes about a variety of issues related to information technology and Internet policy, including digital platforms, e-government, and artificial intelligence. Michael graduated from Wake Forest University, where he majored in Communication with Minors in Politics and International Affairs and Journalism. He received his Master’s in Communication at Stanford University, specializing in Data Journalism.